code: def init_aggregator(self, ctx):
      return AggregatorServerWrapper(ctx)
  
imports: from fate.ml.nn.trainer.trainer_base import HomoTrainerClient, HomoTrainerServer
  from fate.ml.nn.trainer.trainer_base import FedArguments, TrainingArguments
  from dataclasses import dataclass
  from typing import List, Optional, Tuple, Callable, Union
  from fate.arch import Context
  from torch.optim import Optimizer
  from torch.utils.data import Dataset
  from torch.optim.lr_scheduler import _LRScheduler
  from transformers.trainer_callback import TrainerCallback
  from torch.nn import Module
  from torch import nn
  from torch.utils.data import DataLoader
  from transformers import TrainerState, TrainerControl, PreTrainedTokenizer
  from fate.ml.aggregator import AggregatorClientWrapper, AggregatorServerWrapper
  import logging
label_desc: Use image node_id 2 for calling the FedAVGServer obj's underlying member method code with example usage: obj.init_aggregator(ctx) and returns: AggregatorServerWrapper